Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture

Abstract

Abstract. Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use. This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution. Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time. The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.

Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site Wüstebach

“…In this paper, we present the data set obtained in the JFC-2020. It is available via EUDAT (see Heistermann et al, 2022). Section 2 introduces the study area.…”

“…The uncertainty in the neutron counts N (in counts per hour, cph) is based purely on the stochastic nature of the counting process (Zreda et al, 2012;Weimar et al, 2020) and amounts to √ N. Using error propagation theory, the stochastic uncertainty for longer integration periods a (in hours) is Schrön et al, 2018b;Francke et al, 2022). While the uncertainty in soil moisture estimates also propagates through the non-linear conversion function (Weimar et al, 2020;Jakobi et al, 2020), it additionally depends on other processing steps, such as the correction of neutron count rates for atmospheric effects or vegetation and the calibration of the conversion function based on reference measurements (see Sect.…”

“…Within this data infrastructure, the services B2SHARE and B2HANDLE allow users to share data, to manage identifiers, and to provide long-term persistence. Please see Heistermann et al (2022) as a reference to the data repository at the B2SHARE service (https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5 949c63b872). Table 3 links the data subsets in the repository to the corresponding subsections of this paper.…”

“…In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydrogravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al, 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land-atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the…”

Feasibility of Irrigation Monitoring with Cosmic-ray Neutron Sensors

“…Sub-footprint heterogeneity can be reconstructed using multiple instruments, but this comes with increased costs and necessitates further assumptions regarding spatial continuity (Heistermann et al, 2021). As a result, it can be difficult to distinguish local SM variations (Francke et al, 2022), such as the difference between the SM in a small irrigated field and in its surroundings. Furthermore, if the irrigated area is only a small portion of the area sensed by the CRNS, the detection of irrigation-related SM variations might not be possible (Li et al, 2019).…”